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Qwentext->text

Qwen: Qwen2.5 Coder 7B Instruct

Qwen2.5-Coder-7B-Instruct is a 7B parameter instruction-tuned language model optimized for code-related tasks such as code generation, reasoning, and bug fixing. Based on the Qwen2.5 architecture, it incorporates enhancements like RoPE, SwiGLU, RMSNorm, and GQA attention with support for up to 128K tokens using YaRN-based extrapolation. It is trained on a large corpus of source code, synthetic data, and text-code grounding, providing robust performance across programming languages and agentic coding workflows. This model is part of the Qwen2.5-Coder family and offers strong compatibility with tools like vLLM for efficient deployment. Released under the Apache 2.0 license.

Context Window

33K

Input Price

$0.0300/M tokens

Output Price

$0.0900/M tokens

Modality

text->text

Pricing Breakdown
Cost per million tokens for input and output
Input$0.0300/M tokens
Output$0.0900/M tokens

Cost Example: Processing 10,000 input tokens and generating 1,000 output tokens would cost approximately $0.000390

Context Window Size
Maximum tokens the model can process in a single request
Context Window33K tokens
3% of 1M max

~25K

Words Equivalent

~16

Pages of Text

~328

Code Functions

Best Use Cases
What this model excels at
CodingProgrammingDevelopmentMathReasoningAnalysisData-analysisAnalytics

Related Categories:

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